Shock Transmission through International Banks: Austria

Transcription

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WORKING PAPER 199
Shock Transmission through
International Banks: Austria
Esther Segalla
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Shock Transmission through International Banks:
Austria∗
Esther Segalla†
Abstract
This study provides findings on the transmission of liquidity shocks by Austrian parent
banks through the lending channel. I investigate how different types of parent banks adjust
their balance sheet positions in response to a liquidity shock and how such an adjustment
is transmitted into destination countries. I distinguish between three definitions of crossborder lending activities. In the most general definition I analyze changes in total lending,
which consists of the two components - lending to banks and lending to non-banks. In
a second step I concentrate on a narrower definition of lending, that is lending to nonaffiliated banks. Finally I focus on an even more targeted definition, such as lending to
affiliated banks (lending to branches and subsidiaries).
I find that (1) smaller banks (parent banks without affiliates) did not adjust their
balance sheet composition in a very pronounced manner in response to a liquidity shock.
(2) Large banks (parent banks with affiliates) did decrease moderately their cross-border
loan share to other, non-affiliated banks. (3) Internal capital markets are important for
the funding structure of Austrian parent banks and their foreign affiliates. (4) Destination countries matter. Countries signing the Vienna Initiative do receive strong support
through the internal capital market.
Keywords: cross-border lending, liquidity risk, shock transmission, internal capital markets, Vienna Initiative.
JEL classification: E44, F30, G18, G21, G32;
∗
This paper has been written within the framework of IBRN and the author gratefully acknowledges the
support from its members. The analysis has benefited from helpful suggestions and discussions with Helmut
Elsinger, Pirmin Fessler, Markus Knell, Andreas Schicho, Helmut Stix and Michael Strommer. The author
thanks Daniela Michel, Simona Jokubauskaite and Thomas Bergmair for excellent research assistance. The
views expressed in this paper do not necessarily reflect those of the Oesterreichische Nationalbank. All errors
and opinions are the authors sole responsibility.
†
Oesterreichische Nationalbank, e-mail: esther.segalla@oenb.at
Non-technical summary
This study investigates the importance of various lending channels for the transmission of
liquidity risk affecting Austrian banks. The database for this analysis consists mainly of
bank-level balance sheet position that contrast domestic versus cross-border lending activities
for financial institutions with an Austrian banking license. I ask the following questions. Is
a reallocation observable - away from cross-border lending towards more domestic lending
during times of a liquidity shortage? Do larger banks adjust differently to a liquidity shock
than smaller banks? What is the role of internal capital markets within this framework?
The analysis is embedded within the International Banking Research Network (IBRN)
project 2013 and represents the individual country contribution for Austria. IBRN 2013 aims
at analyzing micro-level banking data with a common methodology for 11 countries to explore
the global transmission of liquidity risk. The meta-analysis for all countries, the methodology
and the theoretical underpinning are to be found in Buch and Goldberg (2014).
The Austrian banking sector is quite diverse in terms of banking business models (sectoral
diversification), but also with respect to foreign and domestic ownership structures. Regarding
ownership structures it is necessary to differentiate between active (who is owned by an
Austrian bank) and passive (who owns the Austrian bank) ownership. We observe around 800
incorporated financial institutions, whereby approximately half of the institutions represent
95% of total industry wide assets. The majority of banks has no foreign affiliates (395) and
only a few banks own foreign affiliates (42). The estimation sample introduces a size threshold
and includes therefore 150 banks that have no foreign affiliates, and 36 that do have foreign
affiliates. The majority of Austrian parent banks that actively own foreign affiliates have them
in up to 3 countries (27 Austrian parent banks), 9 Austrian parent banks have affiliates in 4
or more countries, whereof 4 parent banks have affiliates in 14 or more countries.
The analysis uses three definition for cross-border lending activities and compares them to
domestic lending activities. In the most general definition I analyze changes in total lending,
which consists of two components - lending to banks and lending to non-banks. In a second
step I concentrate on a narrower definition of lending, that is lending to banks, whereby lending
to affiliated banks has been excluded. For the last definition I focus on lending to affiliated
banks, such as branches and subsidiaries. I briefly discuss local lending by foreign subsidiaries
in the destination countries.
I find that (1) smaller banks (parent banks without affiliates) did not adjust their balance
sheet composition in a very pronounced manner in response to a liquidity shock. (2) Large
banks (parent banks with affiliates) did decrease moderately their cross-border loan share
to other, non-affiliated banks. (3) Internal capital markets are important for the funding
structure of Austrian parent banks and their foreign affiliates. (4) Destination countries
matter. Countries signing the Vienna Initiative do receive strong support through the internal
capital market.
1
Introduction
This study forms part of the international banking research network initiative (IBRN) and
reports the results for the country study Austria.
The Austrian banking sector is quite diverse in terms of banking business models (sectoral
diversification), but also with respect to foreign and domestic ownership structures. Regarding
ownership structures it is necessary to differentiate between active (who is owned by an
Austrian bank) and passive (who owns the Austrian bank) ownership. I refer to an Austrian
parent bank as a bank that holds an Austrian banking license and resides in Austria (host
country principle). It might actively own foreign affiliates - a branch or a subsidiary - or not.
The term affiliated is used to describe the active ownership link.
The Austrian banking sector has around 800 incorporated financial institutions, whereby
approximately half of the institutions represent 95% of total industry wide assets. The majority of banks has no foreign affiliates (395) and only a few banks own foreign affiliates (42).
The estimation sample introduces a size threshold and includes therefore 150 banks that have
no foreign affiliates, and 36 that do have foreign affiliates. An Austrian bank can be passively
owned by a non-Austrian financial institution. This is the case for 43 banks in the sample, and
the remaining 143 banks are majority owned by Austrian financial institutions. The majority
of Austrian parent banks that actively own foreign affiliates have them in up to 3 countries
(27 Austrian parent banks), 9 Austrian parent banks have affiliates in 4 or more countries,
whereof 4 parent banks have affiliates in 14 or more countries.
The analysis uses three definition for cross-border lending activities and compares them to
domestic lending activities. In the most general definition I analyze changes in total lending,
which consists of two components - lending to banks and lending to non-banks. In a second
step I concentrate on a narrower definition of lending, that is lending to banks, whereby lending
to affiliated banks has been excluded. For the last definition I focus on lending to affiliated
banks, such as branches and subsidiaries. I briefly discuss local lending by foreign subsidiaries
in the destination countries. I ask the following questions. Is a reallocation observable - away
from cross-border lending towards more domestic lending during times of a liquidity shortage?
Do larger banks adjust differently to a liquidity shock than smaller banks? What is the role
of internal capital markets within this framework?
I find that (1) smaller banks (parent banks without affiliates) did not adjust their balance
sheet composition in a very pronounced manner in response to a liquidity shock. (2) Large
banks (parent banks with affiliates) did decrease moderately their cross-border loan share
to other, non-affiliated banks. (3) Internal capital markets are important for the funding
structure of Austrian parent banks and their foreign affiliates. (4) Destination countries
matter. Countries signing the Vienna Initiative do receive strong support through the internal
capital market.
To put the lending definitions into perspective I present some relative magnitudes for
1
2012Q4. I begin with unconsolidated figures. The cross-border total claims represent approximately 75% of the Austrian GDP (231 billion Euros). About half of that (the equivalent of
36% of GDP, 113 billion Euros) are cross-border claims to non-affiliated banks. Loans to affiliated banks amount to 18% of GDP (57 billion Euros). Local claims by foreign subsidiaries
sum up to approximately 95% of GDP (288 billion Euros). If we sums up the volumes of
cross-border total claims, loans to affiliated banks and local claims by foreign subsidiaries, we
approximate the consolidated share of total claims of GDP 163% (503 billion Euros). Figure
2a shows the volumes of the lending definitions over time for the sample representing 95% of
total industry wide assets.
Several analyzes have studied the dynamics in the Austrian banking sector using data
from the Oesterreichische Nationalbank (OeNB). Here I mention just two, which are most
directly aligned in their research theme with the present study. Puhr et al. (2009) find that
cross-border lending to non-banks by Austrian banks expanded rapidly in Central, Eastern
and Southeastern Europe (CESEE) countries from 2002 to 2008. The evidence suggests
complementary effects between direct cross-border lending and indirect lending (through subsidiaries) such that the foreign subsidiary acquires lending business for the parent. Hameter
et al. (2012) use a data set to analyze the credit risks of Austrian Banks in CESEE. The data
consist of the Austrian Central Credit Register. The authors analyze differences in direct
cross-border lending to affiliates and to non-affiliates. Affiliates received more liquidity from
their parent banks than non-affiliates during the 2008/09 financial crisis period.1
I begin the analysis by an introduction to the data base in section 2, followed by graphical
evidence for the three lending definitions in section 3. The analysis continues by embedding
the figurative evidence into a regression framework in section 4 and 5. In section 6 I sum up
the findings.
2
Data
Several data sources consisting of mandatory reports by Austrian financial institutions to the
Oesterreichische Nationalbank (OeNB) have been used. The locational statistics, which builds
the basis for the monthly reports to the Bank of International Settlements (BIS) and several
data sources from the supervisory statistics, such as ownership data and all data relating to
affiliates of Austrian parent banks.2 The individual bank identifier has been anonymized by
the statistical department of the OeNB.
The data mainly contains balance sheet information of financial institutions in Austria. It
includes information on affiliates and cross-border activities across all countries. Concerning
the reporting banks the OeNB employs the “Cutting-Off-The-Tail” principle, which collects
detailed data positions from national financial institutions that represent the national banking
1
For a general overview of statistical evidence concerning the Austrian banking sector see Statistik (2011).
See EZB Monetaer Statistik Regulation (EC) No 25/2009 EZB-MONSTAT. Data reports based on the
Directive 2006/48/EC of the European Parliament and of the Council.
2
2
sector to 95% measured as the total industry wide assets.3 The total banking sector has
around 800 financial institutions. Around 375 banks are included in the “cutting-of-the-tails”
sample. More than 400 banks are very small, domestic banks, with close to zero cross-border
activities. On average 10 banks in the “cutting-of-the-tails” sample have only domestic claims
and no cross-border claims. As the focus of the study relies on cross-border banking activities,
I use the “cutting-off-the-tails” sample as a starting sample. For the main estimations I limit
the sample to include financial institutions, which have a minimum of a balance sheet total
of 0.5 Billion Euros in at least one quarter. The estimation sample includes a total of 186
Austrian parent banks. All descriptive figures have been calculated for the whole sample
and can be provided. For the sample of banks without affiliates (150 banks) we do not have
any information on undrawn credit lines for 14 banks (whereof 10 banks with non-Austrian
passive ownership), which consequently drop out of the estimation. For the sample of banks
with affiliates (36 banks) we have a complete set of information on all the variables.
I construct a panel data set using quarterly series of balance sheet variables for individual banks with the following end of quarter dates: last day of the month of March, June,
September, December of the corresponding year. The panel data set starts 2005Q2 and ends
2012Q4.4 . The data is unconsolidated at the level of each financial institution and is reported
over the full country dimension of foreign claims. Financial institutions report net claims (“net
due from”) and net liabilities (“net due to”) foreign branches. A corresponding position for
the internal capital market between parent bank and foreign subsidiaries needs to be approximated. For this purpose I use the assumption that if an individual bank has a subsidiary in a
particular country at time t, the individual loan position to a bank in that country and time t
is classified as a loan towards the affiliated bank. I use a similar assumption for the “net due
to” liability position regarding foreign subsidiaries. All cross-border claims are then adjusted
such that they exclude claims to the foreign branches and subsidiaries. A positive value of
“net due to” indicates that the parent owes money to its foreign affiliates. Subsidiaries are
included if they are majority owned (ownership percentage larger than 50%) by an Austrian
parent bank. For a detailed description of the variable definitions see the appendix 7. Most of
the descriptive results carry over to consolidated data, where figures are consolidated at the
head institution (holding company). Some of the banking data used for the comparison with
consolidated figures (table 5, figure 2a) are drawn from the OeNB reports to BIS International
Banking Statistics.5
To identify when parent banks are exposed to liquidity shocks, I use information from
the Bank Lending Survey, which surveys the five largest Austrian banks on a regular basis
about individual financing conditions. I have selected the question regarding factors that
3
The OeNB determines once a year during the data collection process for EZB-MONSTAT report, which
financial institutions need to report according to the Cutting-Off-The-Tail principle.
4
The starting date of the data set corresponds to a change in the reporting criteria Monetaer Statistik Ausweisrichtlinie, Beleg 23, V 0413.pdf; Abschnitt: Version 2.0 April 2004
5
The OeNB requires Austrian banks to report consolidated data using different reporting criteria than for
unconsolidated reports. I mainly use unconsolidated data bases for the present study as it allows for a more
refined definition of balance sheet positions and lending channels.
3
affect changes in lending criteria and re-financing costs. Figure 9b plots the aggregate answers of those banks with respect to the relative change in financing conditions. The banks
participating in the survey report a substantial worsening of financing conditions in 2008Q4.6
To understand how the lending and balance sheet of Austrian banks has adjusted during periods of crisis, I present information on banks receiving governmental support. The
Austrian government allowed for a total package of 100 billion Euros consisting of several
rescue measures in November 2008. An independent clearing house (passively owned by the
largest Austrian commercial banks), supported through state liabilities, was incorporated in
the second quarter of 2009 until the first quarter of 2011. The clearing bank AG (OeCAG)
acted like an auction platform to help liquidity enhancing transactions between banks. Furthermore the programm allowed banks access to state liabilities and recapitalization (up to
a total volume of 90 billion Euros) depending on its size of the balance sheet and solvability
(tier 1 capital ratio of at least 7% and equity ratio of at least 10%). 8 large banks made
use of this programm, see table 10. The last measure was a core deposit insurance (volume
of 10 billion Euros), that guaranteed up to 100,000 Euros for private households until 2009,
afterwards without volume limits.
Because bank identifiers are anonymized, I introduce an indicator variable to incorporate
the access to official liquidity providing programmes as of 2008Q4. Even if a bank specific
indicator could be constructed, results are not expected to differ significantly due to the following reasons. On the one hand the largest Austrian-owned banks participated in the rescue
measures, whereby it is unknown how the support measures have been passed through the
sectoral holding structures. Therefore we would need to assume that individual institutions
belonging to the same sector benefited from the head institution participation in the rescue
measures. Moreover there is no time variation in the access of government support across
banks. This would yield two-thirds of the sample (e.g. 25 parent banks with affiliates that
are passively owned by Austrian institutions) to have an indicator of one as of 2008Q4. On
the other hand, foreign-owned banks received government support in their home countries.
These arguments lead me to believe that the indicator variable as of 2008Q4 is qualitatively
not inferior to a bank specific variable indicating access to official funds.
3
Descriptive evidence
The analysis centers around the question how Austrian parent banks are affected by liquidity
shocks and how it is transmitted into different lending channels. For this purpose I present
arguments along three dimensions. In a first step I show results for domestic and cross-border
total lending, whereby total lending decomposes into lending to banks and lending to nonbanks (first dimension). Secondly I take a closer look at the two components and single out
lending to banks (second dimension). In a final step I investigate the role of internal capital
6
For a more detailed description of the EZB bank lending survey see Beer and Waschiczek (2012)
4
markets and differences in the destination country (third dimension). Throughout the analysis
I maintain the differentiation of results by lending behavior for Austrian parent banks, which
own actively foreign affiliates and those, which do not.7
I begin with an overview for the geographical dispersion using the different lending definitions. Figure 1a shows the geographical distribution of cross-border lending activities for
2012Q4 (first definition of lending channel). Germany is the number one destination country
in terms of loan volume and deposit volume from the perspective of an Austrian parent banks.
Whereby Croatia receives the highest loan volume in terms of the country’s GDP.8 Figure
1b shows the volumes and geographical distribution of lending to affiliated banks for 2012Q4
(third definition of lending channel). Croatia, Hungary, Romania and Russia are the most
important destination countries for affiliate lending. In addition figure 5b in the appendix 7
shows the volumes of local claims by foreign subsidiaries. The Eastern European subsidiaries
have substantial local claim volumes (sometimes larger than the direct cross-border lending
through Austrian parent banks). In 2012Q4 the top ranking country in terms of local claims
is the Czech Republic with approximately 40 billion Euros, followed by Russia with 30 billion
Euros and Croatia with 24 billion Euros. Due to differences in reporting requirements of
BIS (e.g. domestic versus foreign ownership of parent institution, local claims defined to be
international or foreign) the volume of cross-border and local claims differ to some extend
between the presented aggregated figures and the published unconsolidated and consolidated
BIS statistics for Austria.
Table 5 in the appendix 7 shows the sum of claims of the Austrian banking sector for
the top destination countries, whereby countries are ranked according to their corresponding
claim volumes. It shows the number of banks and lending volumes for different definitions of
lending channels: cross-border total claims, cross-border claims to affiliates, local claims by
subsidiaries and the consolidated cross-border claims by destination country.
The individual share of loans over total assets remains very stable over the sample period,
whereby the total domestic lending share amount to around 50% and the total cross-border
lending share (excluding lending to foreign affiliates) sums up to 20%.9 Aggregated shares
hide the heterogeneity across banks and their global activities. An important distinction of
banking types is by ownership of foreign affiliates. Austrian parent banks without affiliates
are primarily engaged in domestic banking activities, they are substantially smaller in their
total balance sheet (mean: 1.2 billion Euros in 2012, median: 0.3 billion Euros) than banks
with affiliates (mean: 18 billion Euros, median: 6 billion Euros), they have an average core
deposits ratio of 64% (median: 72%) and an average capital ratio of 12% (median: 11%).
7
In the appendix 7 tables 8 and 9 show the results for the sub-sample of Austrian parent institutions
excluding banks with non-Austrian passive ownership (home country principle).
8
In the appendix 7 I have included the same figure weighted by the GDP of the destination country, see 5a.
In Croatia the cross-border loans share represents more than 10% of it’s GDP. Slovakia has the second highest
share in terms of loan volume of Austrian parent banks of the country’s GDP.
9
The exact aggregate shares vary depending on the sample selection criteria such as the threshold for the
total balance sheet size. Figures for the population of all Austrian banks can be provided by the author.
5
Austrian parent banks with affiliates engage both domestically and abroad (the average
share of aggregate domestic loans over total assets is just below 30% and on average 18% is the
aggregate cross-border border lending share). They have an average core deposit ratio of 35%
(median: 34%) and an average capital ratio of 11% (median: 8%) over the sample period. If
we are interested in a sample split based on total balance sheet size (small versus large banks),
the dividing line is the engagement in cross-border banking paired with ownership of foreign
affiliates. All Austrian banks owning foreign affiliates can be considered to be larger banks,
and all larger banks own foreign affiliates. Figure 2b shows the frequency and geographical
distribution of foreign affiliates and corresponding parent banks. Germany sticks out with a
very large number of branches. Most subsidiaries are located in Eastern Europe.
The heterogeneity of the banking sector becomes apparent if one compares the distribution
of individual domestic and cross-border lending shares over total assets. In the appendix 7 in
figure 9a I show a QQ-plot with the individual share of loans over total assets for each bank,
distinguishing between domestic and cross-border shares of total loans. Concentrating first on
the domestic loan shares, we see that the majority of banks have a share that is larger than the
aggregated share of total domestic loans (the mean aggregated domestic loan share in 2012Q4
is 58%.) Many small banks lend predominantly domestically. The complete opposite holds
for the cross-border lending activities. Only few banks (those above the 80th percentile) have
a share larger than the aggregated share of total cross-border loans (the mean aggregated
cross-border loan share in 2012Q4 is 20%). Due to the skewed distributions of bank-specific
lending shares, I present median shares in most figures.10
In general domestic and cross-border lending activities by the Austrian banking sector
from 2005 to 2012 can be described quite adequately using figure 3. It shows the different
aspects of lending activities along the first two definitions. In figure 3a I plot the median
of individual lending shares differentiating domestic and cross-border lending, in addition to
affiliate ownership. The shares are very stable for banks with affiliates and without. I do not
observe any reallocation or compositional changes in the total lending. In figure 3b I present
the median shares of domestic and cross-border lending to other banks.11 The magnitude of
lending to other banks is around 10% in terms of share of total assets, which corresponds to an
equivalent of 113 billion Euros in volume). A moderately pronounced pattern of reallocation
towards domestic lending, particularly for banks without affiliates, can be observed. I will
revisit this argument using the regression evidence in section 5.
Figure 4 shows the last dimension within my arguments when analyzing how liquidity
shocks have been transmitted into different types of lending. Panel 4a shows the median
of individual lending shares and deposits by Austrian parent banks to its foreign affiliates.
The internal capital market between parent bank and affiliate is substantial in volume. 4%
of total assets in 2012Q4 (503 billion Euros for banks with affiliates) are 21 billion Euros,
10
One can transform the individual share into an aggregated share, by re-weighting each observation with
its bank-specific weight, the weight the particular bank has within the distribution of total assets for all banks.
11
Aggregate shares of non-bank lending remain very stable over the sample period and can be obtained from
the author.
6
which translates to approximately 7% of GDP (see figure 2a and 4a). The graph further
distinguishes between loans to subsidiaries and those to branches, whereby the subsidiaries
dominate the volumes of branches by a multiple. Branches and subsidiaries are substitutes in
terms of ownership structure. Parent banks have either branches in a country or a subsidiary,
not both. The lending share is acyclical between branches and subsidiaries. One can notice
that the median of individual lending shares to subsidiaries is higher in 2009 than the median
share for affiliates (which is the sum of subsidiaries and branches). Parent banks decreased
loans to branches significantly (reporting zero lending, but positive deposits by the branch),
which results in a lower lending share for the median affiliate.
The last figure for this section sets the cross-border lending into relation to affiliate lending
(second and third channels). Figure 4b shows the relative importance of destination countries
by cross-border loans and loans to affiliates over the entire sample period12 Countries far
to the right on the horizontal axis (such as Croatia, Hungary, Italy, Romania, Slovenia and
Russia) but also countries up on the vertical axis (Germany, Great Britain and the non-euro
countries) receive a high volume from the internal capital market of their Austrian parent
banks, but are also important destinations for cross-border lending activities of Austrian
parent banks without affiliates in those countries. The countries in the graph are almost all
countries, where Austrian parent banks own affiliates (except Turkey and the Netherlands)
and correspond with the important destination countries for 2012 from table 5. Branches are
mostly located in the upper, left part of the chart, whereby subsidiaries spread out along the
lower horizontal dimension.
4
Empirical specification
Within the IBRN framework we are interested in the question, which ex-ante balance sheet
characteristics explain best the adjustment of lending growth in response to liquidity shocks.
Throughout we want to highlight differences in the balance sheet adjustments by using information of active ownership features (no affiliates versus affiliates). I start by summarizing
the descriptive evidence from section 3. First I observe very stable domestic and cross-border
total lending shares throughout times of crisis. Second, lending to foreign banks seems to
be a relevant channel of adjustment. Large banks (banks with affiliates) adjust their lending
portfolio more pronounced than smaller banks (banks without affiliates). Third, the role of
internal capital markets is relevant for the overall adjustment in lending growth (cross-border
and affiliate lending are affected).
The empirical strategy attempts to compare changes in domestic, cross-border and net
internal loan positions (balance sheet adjustments) across Austrian parent banks, controlling
for ex-ante exposure of parent banks to liquidity constraints. The idea is to capture the
prior exposure through bank-specific characteristics such as balance sheet size (larger banks
12
Plotting the geographical distribution and importance of destination countries for the year 2012 yields a
similar picture in terms of aspect ratio and lending volumes are one tenth as big as in the here presented figure.
7
have a different access to financial markets than smaller banks), the ratio of illiquid assets
to total assets (a higher share of illiquid assets constraints a bank more in case of a liquidity
shock), the ratio of committed credit lines to total assets (a higher share of off-balance sheet
commitments in previous periods requires more pronounced balance sheet adjustments in
subsequent periods in case of a liquidity shock), the ratio of core deposits over total liabilities
(the higher the core deposit ratio, the less reliance on wholesale deposits, presumably helps a
bank to mitigate effects of a liquidity shock), the ratio of capital over asset (the risk premium
for banks with high capital ratios will be lower, therefore refinancing costs are expected to
be lower) and the potential use of internal capital market fund, such as deposits by affiliates
(the higher the deposit ratio of affiliates, a less pronounced adjustment of the current balance
sheet might be necessary in response to a liquidity shock). The omitted category is wholesale
deposits.
The main regression specification follows the empirical model set out in Buch and Goldberg (2014), wherein changes in different types of lending are regressed on balance sheet
characteristics, measures of liquidity risk, and information on public interventions.
∆Yit = γi + µt + (β 0 + β 1 LIB OISt )Xi,t−1 + (α0 + α1 LIB OISt ∗ Xi,t−1 )Fit + it
(1)
Xi,t−1 is a vector of lagged control variables that capture the degree to which a bank is exposed
to liquidity risk through ex-ante balance sheet characteristics such as liquid asset share, the
share of core-deposits in bank funding, bank size, the share of outstanding commitments, and
through internal capital markets.
Liquidity shocks are approximated using the Libor over overnight indexed swap rates
(LIB OISt ), whereby an increase in the spread relates to increased liquidity funding risk
and this applies to all Austrian banks uniformly. During the sample period the Austrian
government provided all Austrian banks with access to banking rescue packages from the last
quarter of 2008 onwards. For an overview of individual Austrian banks that have actually participated in rescue measures see table 10 in the appendix 7. The access to additional liquidity
through recapitalization by the government poses a challenge for the empirical identification
during crisis times. I present estimation results allowing slopes to be different after official
sector liquidity has been provided to Austrian parent banks. Official sector liquidity has been
provided to the largest banks shortly after 2008Q4. The indicator variable “official use” is a
time indicator to incorporate the access to official liquidity providing programmes to all banks
as of 2008Q4.13
Table 2 and table 3 present the marginal effects of the balance sheet variables (illiquid
assets, commitment ratio, log real assets, core deposit ratio, tier 1 capital, net due from
affiliated banks) of Austrian parent banks with and without affiliates interacted with the
Libor-Ois spread (column: not utilized), the additional interaction with access to central bank
13
The empirical variable description “utilized” versus “non-utilized” is for the Austrian case a bit misleading,
as it is not a bank specific variable for governmental liquidity support, but rather a sectoral indicator of
governmental liquidity support.
8
facilities (column: utilized) and the difference between the two effects (column: difference).
The interaction of the balance sheet variables with the Libor-Ois spread allow to differentiate
in the sensitivity of responses to a liquidity shock between banks with different balance sheet
characteristics. The additional interaction of a particular balance sheet variable with LiborOis spread and with the official use indicator variable provides insights into changes in the
sensitivity for periods after the crisis of 2008. Table 2 uses domestic and cross-border total
loan growth as dependent variable and table 3 uses cross-border bank loan growth.
I exploit the geographical dispersion of destination countries (for parent-subsidiary pairs
only, no foreign branches are included) to analyse the relative adjustments of parent banks
exposed to liquidity risk using a variant of the following specification:
∆Yitc =γi + µct +
c
c
(β 0 + β 1 ∗ LIB OISt + β 2 ∗ Xi,t−1
+ β 3 ∗ LIB OISt ∗ Xi,t−1
)Xi,t−1 +
c
(α1 ∗ LIB OISt + α3 ∗ LIB OISt ∗ Xi,t−1
) ∗ Xi,t−1 ∗ Fit +
(2)
it
The dependent variable is the growth rate of “net due to” foreign subsidiaries in a particular
destination country. Now the panel dimension consists of parent-foreign-subsidiary bank at
each quarter over the distribution of foreign subsidiaries’ countries. The sample is split into
parent-foreign-subsidiaries’ countries that have signed the Vienna Initiative and those which
c
have not. The independent variable Xi,t−1
consists of loans by the foreign subsidiary to
it’s Austrian parent bank. The idea is that global banks adjust their lending relative to
characteristics of their foreign subsidiaries depending on the subsidiaries’ location. Table 4
presents the results for this estimation. The estimation equation includes destination country
- time fixed effects to absorb changes in demand conditions. By construction the sample
includes only destination countries where at least two distinguished parent-foreign subsidiary
pairs are present.
5
Empirical results
Lets begin with responses to liquidity shocks by Austrian parent banks without affiliates in
panel A of table 2. The first three columns show the change in domestic loans, the latter
three columns the change of cross-border loans as the dependent variable. For a higher price
of market liquidity, banks with an ex-ante higher commitment ratio decreased their domestic
lending (-0.258**), something that was reversed after the crisis (difference: +0.372*) Banks
with higher core deposit ratios, reduced their cross-border lending positions for increasing
liquidity prices (-0.065*). Whereby the core deposit ratio has no significant impact on crossborder lending growth after 2008 (difference +0.069**).
Panel B shows the results for Austrian parent banks with affiliates, where banks with
higher commitment ratios had no effect on domestic lending before the crisis, but increased
9
their domestic lending share (+0.227*) after the crisis. With respect to their cross-border
lending positions there seem to be some offsetting tendencies at work. For a given market
liquidity price, banks with a higher commitment ratio increase their cross-border loan share
(+0.248**) before the crisis, but decrease it sharply (difference: -0.442***), whereby banks
that receive net-deposits from their affiliates decrease it (net due from: -0.260*) also through
the crisis (net due from: -0.137*). I interpret the effects for the internal capital market
variable that banks that receive higher deposits from affiliates (compared to other banks with
affiliates) adjust their loan portfolio after the crisis more towards Austria.
Summing up - which balance sheet characteristics are most responsive to changes in liquidity pricing on loan growth? Changes to the composition of domestic and cross-border
total lending shares during times of higher liquidity financing can only be described as being
very moderate, which is also suggested by graph 3a. Small banks (without affiliates) with
higher commitment ratios decrease domestic total lending, those with higher core deposits decrease their cross-border total lending, relative to other banks without affiliates. Large banks
(with affiliates) with higher commitment ratios increase cross-border total lending, those with
higher deposits from affiliates decrease cross-border total lending, relative to other banks with
affiliates.
Table 8 in the appendix 7 show the results excluding non-Austrian owned parent institutions. How are Austrian parent institutions that are majority owned by Austrian institutions
(home country principle) different from all Austrian parent institutions? In the top 10 of
the largest banks in Austria several are non-Austrian majority owned parent institutions (total assets in billion Euros mean: 27.8, median: 3.3). These banks have a median share of
cross-border loans over total assets of 41.7% (domestic median share: 11.4%) compared to
Austrian majority owned banks with a median cross-border share of 18.3% (domestic median
share: 51.1%). If we exclude the non-Austrian owned parent institutions the estimation sample consists of 114 banks without affiliates and 25 banks with affiliates. Although divergent
in some aspects the broad pattern of the results description remain intact. A sample split
based on non-Austrian ownership has also it’s caveats as some of the largest Austrian banks
have experienced an ownership change in response to the strained liquidity situation.
So far I have analyzed total lending shares, which is a composite term consisting of lending
to banks and non-banks. Graph 3b indicates that particular lending to other banks appears
to be the more sensitive part. The median cross-border bank lending share is around 8%
for parents with affiliates, but only 0.004% for parent banks without affiliates. The median
domestic bank lending share for parents with affiliates is 8% and for parents without affiliates
12%. I turn to table 3, where the dependent variable is changes in cross-border bank loans by
Austrian parent banks without (first three columns) and with affiliates (latter three columns).
Comparing the results from the cross-border estimations (total lending as the dependent
variable) and now the results with the change in bank lending as the dependent variable, it
seems that the changes in total lending are essentially the result from adjustments in bank
lending by large parent banks - banks with affiliates (size: -0.012**). The differences between
10
periods where banks had access to official liquidity provision or not for the commitment
ratio and the deposit ratio are quite large (commitment ration: -0.294**, deposit ratio: 0.097*). Parent banks which received larger deposit transfers from their affiliates, did reduce
their cross-border lending (-0.124*) more compared with banks that received less internal
funds during times of crisis. Smaller banks (banks without affiliates) did not adjust their
cross-border financial lending activities in any pronounced way, whereby banks with affiliates
decreased their cross-border financial lending shares in response to higher liquidity costs.
This leads us to question the role of internal capital markets. If Austrian parent banks
decreased their cross-border lending to non-affiliated foreign financial institutions, did they
adjust their internal capital flows in a similar manner? Figure 4a shows the total volume of
loans to affiliates overtime. The aggregated volume of loans over all Austrian parent banks
to their affiliates (either branch or subsidiary) is 57 billion Euros for 2012Q4. The median of
net due to (internal capital market loans minus deposits) is 0.18 billion Euros over the whole
sample period and 0.08 billion euros in 2012Q4. Affiliates and parent banks make extensive
use of reallocation of funds. The decomposition of affiliate lending into loans to branches and
loans to subsidiaries show that the flows of fund are not synchronic. I investigate the extend
of changes in net due to parent banks balance sheet characteristics using panel D in table 3.
The coefficient for deposits from affiliates remains negative (for the sample excluding nonAustrian owned parent institution the coefficient becomes significant negative). Suggesting
that banks with a relatively high share of net deposits of affiliates compared to other banks
with affiliates, lend less to affiliates. Suggesting a fund retrieval towards the Austrian parent
institution, when liquidity becomes more expensive. But the regression uses parent bank net
flows to affiliate aggregating over all countries of its ownership structure. This aggregates
out all differences with respect to a ranking of affiliates within the global banking structure
of a particular bank. It seems that this set-up aggregates over many important features,
such as not distinguishing between affiliate types (branches and subsidiaries) and ignoring the
importance of country destinations.
Ultimately I want to analyze wether shock transmission differs by destination countries
concentrating on one particular affiliate relationship - the subsidiary. I exploit variation from
a policy, the “Vienna Initiative”, which coordinated multinational banks, country supervisors,
central banks, governments and international organizations to achieve stable funding for subsidiary countries at risk during the financial crisis. 5 countries (Bosnia-Herzegovina, Hungary,
Latvia, Romania, Serbia) signed an agreement with the 5 (among others) largest Austrian
parent banks having subsidiaries in those countries to ensure that interbank liquidity would
not dry up. The Austrian parent banks have committed themselves to keep their subsidiaries
capitalized, providing them with sufficient liquidity. For an overview of the Vienna Initiative
and its impact on host countries see Haas et al. (2014).
As five Austrian banks have voluntarily participated in the initiative, I exploit the variation over the ownership structure, all destination countries and the countries directly affected
by the Vienna Initiative agreements. I would expect subsidiaries net lending in countries,
11
which have signed the Vienna Initiative to be less affected during times of higher liquidity
costs even for the Austrian parent bank. Table 4 shows regression results over the complete
country dimension of parent banks-affiliates-destination countries. The first three columns are
the sample of countries, which have not signed the Vienna Initiative agreement. The latter
three columns represent the estimation for countries, which have indeed signed the agreement.
7 Austrian parent banks have 39 subsidiaries in the five Vienna Initiative countries. If a parent
bank has several subsidiaries per country and date, I implicitly assume one subsidiary per date
and country. This becomes necessary due to the fact that I need to approximate lending from
the parent bank to the subsidiary. Among the already large banks with affiliates, the largest
ones are engaged in those countries. I find the illiquid asset ratio, the commitment ratio, the
size, the tier 1 capital ratio and the net due from ratio to be relevant balance sheet characteristics to explain changes in the net due to ratio. Parent banks with ex-ante high net due
from ratios (deposits from the subsidiary to the Austrian parent bank), higher capitalization
and higher commitment ratios, increase their net lending to subsidiaries after the Vienna Initiative was negotiated (net due from: +0.506**, commitments: +0.028*, capital: +0.506**)
compared to banks with lower ratios during times of liquidity shortages. Larger parent banks,
with higher commitment ratios and higher capital ratios decreased their net lending to foreign
subsidiaries (difference capital: -0.079*, difference commitments: -0.073*). Yet higher deposit
ratios from subsidiaries increased their net lending to subsidiaries (+0.108**) after 2008. It
confirms that parent banks prioritize internal funds allocations to subsidiaries according to
their importance within the organizational structure.
6
Conclusions
Do banks adjust to worsening conditions by shifting credit growth towards their home market? How does this translate through the business structure of global banks? This study
investigates how Austrian banks adjust their balance sheet positions in response to a tighter
liquidity providing environment. I distinguish between three definitions of cross-border lending such as total lending, lending to non-affiliated banks and lending to affiliated banks. I find
that (1) smaller banks (parent banks without affiliates) did not adjust their balance sheet
composition in a very pronounced manner in response to a liquidity shock. (2) Large banks
(parent banks with affiliates) did decrease moderately their cross-border loan share to other,
non-affiliated banks. (3) Internal capital markets are important for the funding structure of
Austrian parent banks and their foreign affiliates. (4) Destination countries matter. Countries
signing the Vienna Initiative do receive strong support through the internal capital market.
12
Figure 1: Lending types across the World
(i) Map 1a shows the volume of cross-border loans (excluding loans to affiliates) of Austrian parent banks for
2012Q4 by its geographical distribution. (i) Both maps 1a and 1b includes only Austrian parent banks with
a minimum of 500 Mio. Euros balance sheet sum at least once during the sample period. (iii) The bottom
part of map 1a shows an enlarged picture of Europe and bracket figures in the legend show the number of
countries in each category. (iv) Map 1b shows figures for European affiliates only. At the bottom of the legend
the affiliate countries excluded of the map are documented.
(a) Cross-border Lending Q4 2012
Loans(in bn Euros)
.001 - .01 (26)
.01 - 1 (72)
1 - 5 (19)
5 - 15 (9)
15 - 40 (1)
No data (127)
(b) Lending to Affiliates Q4 2012
Loans to Affiliates
(in bn Euros)
.001 - .01 (0)
.01 - 1 (13)
1 - 5 (7)
5 - 15 (2)
15 - 40 (0)
No data (24)
not included in the map: CN(.23) HK(.25) KZ(.39) MY(.39) RU(3.0) SG(1.8) US(.004)
13
Figure 2: Aspects of the Austrian Banking Sector
(i) Figure 2a shows the aggregated volumes of the Austrian banking sector for the different lending channels
for the “cutting-off-the-tails” sample (375 banks). (ii) It includes cross-border, unconsolidated claims (dashed
line), unconsolidated loans to affiliated foreign banks (internal capital market, solid light blue line), local unconsolidated claims by foreign subsidiaries (dash-dotted line) and cross-border consolidated claims of Austrian
parent banks (dark blue solid line). (iii) Summing up the three unconsolidated volumes of claims approximates
the consolidated volume of claims. (iv) Figure 2b shows the geographical distribution of affiliates and their
Austrian parent banks. It distinguishes affiliates between foreign branches and foreign subsidiaries. (v) Some
countries were grouped together to maintain data protection requirements.
(a) Comparison of Lending Volume
01
2
2
1
D
ec
n-
-2
20
1
20
1
D
Ju
nJu
ec
-
20
11
01
0
0
-2
01
ec
n2
Cross-Border Claims(C)
Local Claims
D
ec
D
Ju
-2
00
9
00
9
08
n2
D
Ju
ec
-
n20
20
08
7
D
Ju
ec
20
0
-2
00
7
06
-2
0
Ju
n-
00
6
D
Ju
D
ec
n2
-2
ec
Ju
n-
20
05
00
5
0
Claims Volume in bn Euros
200
400
600
Consolidated and Unconsolidated Claims of AT Parent Banks
Cross-Border Claims (UC)
Loans to Affiliates
Affiliates
14
Parents
SUB
BRA
st
SUB
BRA
re
ro
SUB
BRA
BG
no
H
n
Eu
SUB
BRA
PL
SUB
BRA
SUB
BRA
SUB
BRA
M
T
U
A
R
U
SUB
BRA
w
e
SUB
BRA
cs
SUB
BRA
BA
SUB
BRA
H
R
SUB
BRA
SI
SUB
BRA
SUB
BRA
IT
/R
U
SK
SUB
BRA
O
SUB
BRA
Z
C
D
E
SUB
BRA
0
20
40
60
80
(b) Geographical Distribution of Affiliate Ownership
Figure 3: Domestic and Cross-border Lending Shares
(i) Figure 3a shows the median shares of domestic and cross-border total lending over total assets overtime (red
is domestic, blue is cross-border). (ii) Figure 3a differentiates between parent banks with affiliates (solid line)
and without affiliates (dashed line). (iii) Figure 3b shows the median shares of domestic and cross-borderbank
lending over total assets and overtime (red is domestic, blue is cross-border). (iv) Figure 3b differentiates
between parent banks with affiliates (solid line) and without affiliates (dashed line).
(a) Median Share of Loans
Domestic wo. Affiliates (2)
Cross-Border w. Affiliates (3)
Cross-Border wo. Affiliates (4)
2
01
2
1
-2
ec
D
-2
01
01
Domestic w. Affiliates (1)
Ju
n
nJu
D
ec
-2
20
1
1
10
20
01
-2
ec
-
Ju
n
D
ec
D
-2
20
0
00
9
09
8
D
Ju
ec
n-
-2
20
00
08
07
nJu
D
ec
20
-2
0
07
06
D
Ju
n-
06
-2
0
ec
20
n-
-2
Ju
D
Ju
ec
n-
20
00
05
5
.1
.01
.2
.11
.21
Shares for (4)
Shares for (1)(2)(3)
.4
.3
.6
.5
.7
.31
Cross-Border and Domestic Loans of AT Parent Banks
(b) Median Share of Loans to Banks
Cross-Border w. Affiliates (1)
Domestic wo. Affiliates (2)
Domestic w. Affiliates (3)
Cross-Border wo. Affiliates (4)
Source: OeNB
15
20
12
ec
D
-2
01
2
Ju
n
-2
01
1
0
20
11
ec
D
Ju
n-
-2
01
0
ec
-2
01
D
Ju
n
D
n20
0
Ju
ec
9
-2
00
9
8
-2
00
20
08
ec
D
Ju
n-
20
07
00
6
-2
00
7
ec
D
Ju
n
00
6
ec
-2
D
20
0
n2
Ju
ec
D
Ju
n
-2
00
5
5
0
Shares for (1)(2)(3)
.05
.1
.0002
.0004
.0006
Shares for (4)
.15
.0008
Cross-Border and Domestic Loans to Banks of AT Parent Banks
Figure 4: Cross-Border and Affiliate Lending Shares
(i) Figure 4a shows the median shares of loans to affiliates over total assets overtime (solid dark line). (ii)
Figure 4a shows the median shares of deposits by affiliates over total assets overtime (solid light line). (iii)
Figure 4a differentiates between loans to subsidiaries (dash-dotted line) and loans to branches (dotted line).
(iv) Figure 4b shows the volume of cross-border loans on the vertical axis and the volume of loans to affiliates
on the horizontal axis by country over the whole sample period. (v) The top 15 destination countries based
on 2012Q4 cross-border loan volume are represented and therefore the country distribution is not exclusively
limited to countries with affiliates.
(a) Median Share of Loans and Deposits to Affiliates
Loans to Affiliates
Loans to Subsidiaries
Deposits by Affiliates
Loans to Branches
n-
12
20
ec
D
20
12
11
ec
D
Ju
-2
0
11
0
20
01
nJu
10
20
D
ec
-2
09
D
Ju
n-
ec
-
20
09
8
-2
nJu
ec
D
20
00
08
7
20
nJu
-2
ec
D
Ju
n-
-2
20
00
07
6
00
06
ec
D
ec
-2
0
00
-2
20
n-
D
Ju
Ju
n
05
5
Share of Loans/Deposits to Affiliates
.02
.04
.06
.01
.05
.03
Internal Capital Market of AT Parent Banks
Source: OeNB
(b) Importance of Destination Countries
DE
GB
we
PL
TR
BG
BA
0
CZ
SK
50
RO
SI
rt
RU
MT
UA
cs
HR
IT
ne
NL
0
Cross-Border Loans in bn Euros
500
1000
Cross-Border Loans and Loans to Affiliates
of AT Parent Banks
100
150
Loans to Affiliates in bn Euros
ne: CN, HK, MY, SG, UK, US, NO, GI
rt: AL, BY, CY, KG, KY, KZ, LI, LV, MK, TJ
Source: OeNB
16
cs: CS, RS, XK, ME
we: FR, PT, ES, CH
HU
200
Table 1: Summary Statistics for Austrian Banks over 2005Q2 to 2012Q4
Percent (unless otherwise specified)
Austrian-owned parent Banks
No affiliates(n=118)
Variable
Mean
Median
SD
Foreign-owned parent Banks
With foreign affiliates(n=25)
Mean
Median
SD
No affiliates(n=32)
Mean
Median
SD
With affiliates(n=11)
Mean
Median
SD
Balance sheet data (for each bank / and quarter i)
Observations
Dependent Variables
∆ Liquid Assets/TA
∆ Domestic Loans/TA
∆ Foreign Loans/TA
∆ Local Claims 1/TA
∆ Net Due to Affiliates/TA
3,239
587
765
256
0.000
0.008
0.000
0.006
0.020
0.004
0.001
0.006
0.003
0.003
0.001
0.000
0.000
0.006
0.002
0.000
0.000
0.000
0.007
0.020
0.006
0.011
0.003
0.007
0.001
0.009
0.002
-0.000
0.004
0.000
0.014
0.026
0.006
-0.000
0.004
0.004
0.004
0.001
-0.000
-0.000
0.000
0.008
0.001
0.000
0.000
0.012
0.021
0.007
0.013
0.004
0.007
0.757
0.085
2.866
3.222
0.570
0.095
0.064
0.706
0.761
0.079
0.863
0.994
0.647
0.095
0.026
0.723
0.127
0.043
5.652
5.789
0.250
0.053
0.116
0.166
0.685
0.096
17.333
16.273
0.360
0.085
0.179
0.517
0.034
0.708
0.094
8.101
7.597
0.329
0.080
0.182
0.510
0.010
0.151
0.045
24.143
23.918
0.207
0.054
0.106
0.179
0.090
0.802
0.092
1.279
1.283
0.492
0.093
0.428
0.469
0.894
0.031
0.762
0.685
0.612
0.048
0.388
0.381
0.231
0.136
1.438
1.670
0.384
0.158
0.387
0.362
0.583
0.077
27.907
19.274
0.343
0.098
0.419
0.184
0.039
0.612
0.048
3.288
4.246
0.350
0.084
0.395
0.115
0.008
0.184
0.075
46.236
37.540
0.261
0.071
0.236
0.176
0.081
17
0.000
0.009
0.001
Independent Variables
Illiquid Assets/TA
Commitments/TA+Com
Real Assets (in BN Euros)
Real Assets 4Q 2012 (in BN Euros)
Deposits/Liabilities
Capital/TA
Foreign Loans/TA
Domestic Loans/TA
Deposits from Affiliates/TA
(i) Source: OeNB.
(ii) Beginning of quarter assets are used to standardize growth in all dependent variables.
(iii) The data are observed quarterly from 2005Q1 to 2012Q4 for a panel of individual banks, which report unconsolidated figures.
(iv) The sample is restricted to banks with greater than 0.5 billion Euros in total assets (2012 prices) at least once in a quarter.
(v) The dependent variables are winsorised at the 1st and 99th percentile.
(vi) To mitigate the effect of bank mergers on the dependent variable, banks are excluded in a particular quarter when asset growth exceeds 10%.
(vii) Affiliates include foreign branches and subsidiaries of Austrian parent banks.
(viii) The appendix 7 provides the same table with winsorised and outlier corrected variables.
Table 2: Domestic and Cross-border Lending Activities
This table reports the marginal effects of liquidity risk conditions and central bank credit facility access on
firm characteristics’ effects on growth in domestic and cross-border total loans (to banks and non-banks) for
parent banks without affiliates (upper panel) and parent banks with affiliates (lower panel). The underlying
fixed effects regressions of quarterly growth in total loans on Libor-Ois, central bank facility access, firm
characteristics, and interactions are presented in appendix 7. Beginning of quarter assets are used to
standardize growth in loans. The data are observed quarterly from 2005Q1 to 2012Q4 for a panel of individual
banks, which report unconsolidated figures. The panel is restricted to banks with greater than 0.5 billion
Euros in total assets (2012 prices) at least once in a quarter during the sample period. To mitigate the effect
of bank mergers on the dependent variable, banks are excluded in a particular quarter when asset growth
exceeds 10%. Firm characteristics data comes from a variety of supervisory data sources provided by OeNB.
The Libor-Ois is the quarterly average of the daily difference between the London Interbank Offered Rate and
the effective federal funds rate. Growth variables are winsorized at the 1st and 99th percentiles. Standard
errors are clustered by bank. ***, **, and * respectively indicate significance at the 1%, 5%, and 10% level.
Panel A: Austrian Parent Banks without Affiliates
∆ Domestic Loans
Central Bank Facility Access
∆ Loans/Assets
Illiquid Assets
Commitment
Log Real Assets
Deposits
Capital
Observations
Number of Banks
R2 within
R2 between
R2 overall
Time fixed effects
Bank fixed effects
Not Utilized
0.002
-0.258**
0.007*
0.017
-0.011
3,457
136
0.067
0.139
0.023
Yes
Yes
Utilized
0.000
0.114
-0.003
-0.017
-0.046
Difference
-0.002
0.372*
-0.010
-0.035
-0.035
Panel B: Austrian Parent Banks with Affiliates
∆ Domestic Loans
∆ Loans/Assets
Illiquid Assets
Commitment
Log Real Assets
Deposits
Capital
Net Due To
Observations
Parent Banks
R2 within
R2 between
R2 overall
Time fixed effects
Bank fixed effects
Not Utilized
-0.008
0.094
-0.005
-0.006
-0.218
0.144
777
36
0.136
0.001
0.024
Yes
Yes
Utilized
-0.013
0.227*
-0.009*
-0.040
0.091
0.255
Difference
-0.005
0.134
-0.005
-0.034
0.309
0.112
18
∆ Cross-Border Loans
Not Utilized
-0.064
0.110
-0.008
-0.065*
0.017
3,368
133
0.052
0.001
0.003
Yes
Yes
Utilized
-0.013
0.052
0.002
0.004
0.021
Difference
0.050
-0.058
0.010*
0.069**
0.004
Not Utilized
-0.042
0.248**
-0.017***
-0.032
-0.323
-0.260*
777
36
0.133
0.026
0.018
Yes
Yes
Utilized
0.080
-0.194
-0.002
-0.091**
0.052
-0.137*
Difference
0.122
-0.442***
0.015*
-0.060
0.375
0.123
Table 3: Cross-border Lending Activities to Banks
firm characteristics’ effects on growth in cross-border loans to banks for parent banks without affiliates and
banks with affiliates (upper panel) and net-due to affiliates for parent banks with affiliates (lower panel).
Affiliates are foreign branches and foreign subsidiaries of parent banks. The underlying fixed effects regressions
of quarterly growth in loans to banks on Libor-Ois, central bank facility access, firm characteristics, and
interactions are presented in appendix 7. Beginning of quarter assets are used to standardize growth in
loans. The data are observed quarterly from 2005Q1 to 2012Q4 for a panel of individual banks, which report
unconsolidated figures. The panel is restricted to banks with greater than 0.5 billion Euros in total assets
(2012 prices) at least once in a quarter during the sample period. To mitigate the effect of bank mergers on
the dependent variable, banks are excluded in a particular quarter when asset growth exceeds 10%. Firm
characteristics data comes from a variety of supervisory data sources provided by OeNB. The Libor-Ois is the
quarterly average of the daily difference between the London Interbank Offered Rate and the effective federal
funds rate. Growth variables are winsorized at the 1st and 99th percentiles. Standard errors are clustered by
bank. ***, **, and * respectively indicate significance at the 1%, 5%, and 10% level.
Panel C: Austrian Parent Banks without Affiliates and with Affiliates
Banks without Affiliates
Banks with Affiliates
∆ Loans
Illiquid Assets
Commitment
Log Real Assets
Deposits
Capital
Net Due To
Observations
Parent Banks
R2 within
R2 between
R2 overall
Time fixed effects
Bank fixed effects
Not Utilized
Utilized
Difference
Not Utilized
Utilized
Difference
-0.065
0.071
-0.006
-0.050*
0.041
-0.008
0.118*
-0.002
-0.006
-0.020
0.057*
0.047
0.004
0.044
-0.061
-0.010
0.167
-0.012**
0.001
-0.216
-0.125
0.055
-0.127
-0.004
-0.096***
0.180
-0.124*
0.065
-0.294**
0.008
-0.097*
0.397
-0.004
3,390
135
0.040
0.000
0.005
Yes
Yes
777
36
0.141
0.046
0.015
Yes
Yes
Panel D: Austrian Parent Banks with Affiliates
∆ Net Due
Illiquid Assets
Commitment
Log Real Assets
Deposits
Capital
Net Due To
Observations
Parent Banks
R2 within
R2 between
R2 overall
Time fixed effects
Bank fixed effects
Not Utilized
0.033*
0.055
-0.005
-0.020
0.062
-0.022
777
36
0.119
0.030
0.011
Yes
Yes
Utilized
-0.009
-0.167
0.007*
0.008
-0.066
-0.171
Difference
-0.042
-0.222*
0.012**
0.029
-0.129
-0.148
19
Table 4: Austrian Parent Banks with Affiliates across Country Dimension
firm characteristics’ effects on growth in net-due to subsidiaries for parent banks with subsidiaries. The panel
dimension consists now of parent banks at each quarter over the distribution of subsidiaries’ countries. The
sample is split into countries, which have not signed the Vienna Initiative (Non-VI Countries in the first
three columns) and countries, which have signed the agreement (VI countries in the last three columns). The
variable “due from” refers to loans of the individual foreign subsidiary to it’s Austrian parent bank. The
underlying fixed effects regressions of quarterly growth in net to to on Libor-Ois, central bank facility access,
firm characteristics, and interactions are presented in appendix 7. Beginning of quarter assets are used to
standardize growth in net due to. The data are observed quarterly from 2005Q1 to 2012Q4 for a panel of
individual banks, which report unconsolidated figures. The panel is restricted to banks with greater than 0.5
billion Euros in total assets (2012 prices) at least once in a quarter during the sample period. To mitigate
the effect of bank mergers on the dependent variable, banks are excluded in a particular quarter when asset
growth exceeds 10%. Firm characteristics data comes from a variety of supervisory data sources provided by
OeNB. The Libor-Ois is the quarterly average of the daily difference between the London Interbank Offered
Rate and the effective federal funds rate. Growth variables are winsorized at the 1st and 99th percentiles.
Standard errors are clustered by bank. ***, **, and * respectively indicate significance at the 1%, 5%, and
10% level.
Panel E: Austrian Parent Banks with Affiliates across Country Dimension
Non VI Countries
VI Countries
∆ Net Due
Illiquid Assets
Commitment
Log Real Assets
Deposits
Capital
Due from
Observations
Number of Banks
R2 within
R2 between
R2 overall
Time fixed effects
Bank fixed effects
Country fixed effects
Not Utilized
0.006
0.018
-0.001*
-0.012
0.049*
-0.094
1,395
70
0.072
0.028
0.003
Yes
Yes
Yes
Utilized
0.005
-0.055**
0.002*
-0.002
-0.030
0.108**
Difference
-0.001
-0.073*
0.003**
0.010
-0.079*
0.202
20
Not Utilized
0.013*
0.031
-0.001*
0.002
-0.009
0.408
619
25
0.169
0.072
0.085
Yes
Yes
Yes
Utilized
-0.007
0.028*
-0.001
-0.001
0.027***
0.506**
Difference
-0.020*
-0.003
0.000
-0.003
0.036
0.098
References
C. Beer and W. Waschiczek. Analyzing corporate loan growth in Austria using bank lending survey data conceptual issues and some empirical evidence. Monetary Policy and the
Economy OeNB, pages 61–80, 2012.
Bericht des Rechnungshofes. Bankenpaket. (2012/9).
C. Buch and L. Goldberg. International banking and liquidity risk transmission: Lessons from
across countries. Staff Reports, (675), May 2014.
R. De Haas, Y. Korniyenko, A. Pivovarsky, and T. Tsankova. Taming the herd? Foreign
banks, the vienna initiative and crisis transmission. Journal of Financial Intermediation,forthcoming, 2014.
M. Hameter, M. Lahnsteiner, and U. Vogel. Intra-group cross-border credit and roll-over risks
in cesee - Evidence from Austrian banks. Financial Stability Report, (23):76–93, 2012.
C. Puhr, M.S. Schwaiger, and M. Sigmund. Direct cross-border lending by Austrian banks to
eastern europe. Financial Stability Report, (17):61–80, 2009.
Oesterreichische Nationalbank Statistik. Bankenstatistisches Jahrbuch. 2011.
21
7
Appendix A
Table 5: Structure and Importance of Destination Countries 2012Q4
Country
DE
GB
IT
PL
FR
HR
CH
TR
NL
US
RO
CZ
SI
HU
RU
SK
LU
KY
CY
ES
BG
BE
UA
CS
SG
SE
IE
DK
BA
Unconsolidated
Cross-Border Parents
Rank Banks Claims
1
358
47.42
2
326
17.63
3
315
12.53
4
245
11.34
5
287
11.28
6
220
9.98
7
342
9.54
8
118
9.47
9
305
9.01
10
334
8.27
11
185
7.82
12
284
7.78
13
195
6.72
14
304
6.24
15
191
5.06
16
260
4.73
17
186
4.19
18
55
3.40
19
102
3.04
20
238
2.91
21
133
2.26
22
214
2.20
23
117
2.08
24
153
1.97
25
92
1.95
26
260
1.76
27
152
1.69
28
165
1.34
29
160
1.24
Loans
0.84
0.79
0.29
0.56
0.59
0.94
0.92
0.70
0.46
0.36
0.89
0.84
0.93
0.71
0.92
0.57
0.34
0.64
0.98
0.42
0.88
0.58
0.66
0.87
1.00
0.27
0.18
0.40
0.93
Unconsolidated
Affiliates
Banks Claims
91
2.78
<4
1.14
<4
3.02
<4
0.21
<4
0.27
9
8.74
4
0.78
.
.
<4
0.02
5
6.92
25
1.75
11
3.43
14
5.27
4
5.49
12
1.14
.
.
.
.
<4
2.34
.
4
3.26
7
1.63
<4
1.81
<4
0.00
.
.
9
1.24
Loans
0.81
1.00
0.82
0.12
0.20
0.64
0.97
1.00
0.95
0.39
0.84
0.88
0.55
0.53
0.38
0.63
0.59
1.00
0.52
Unconsolidated
Subsidiaries Local
Banks
Claims
<4
3.86
.
<4
3.01
<4
0.11
<4
0.27
9
24.18
<4
0.05
.
.
.
4
18.59
5
40.28
5
6.87
8
18.73
4
30.46
5
18.03
.
.
.
.
<4
7.36
.
4
6.47
7
6.31
.
.
.
.
9
15.43
Consolidated
Rank Banks Claims
2
59
44.38
10
52
17.83
8
50
20.62
9
42
20.55
12
47
11.95
3
41
38.80
19
56
9.47
18
29
9.69
17
51
9.75
13
52
11.29
5
38
34.51
1
47
62.34
11
42
14.34
7
46
29.03
4
39
35.68
6
43
31.22
22
46
4.53
24
22
4.25
25
37
3.34
26
41
3.24
14
33
10.76
27
51
2.20
15
19
10.41
20
24
9.16
40
23
1.23
33
43
1.75
32
38
1.92
38
41
1.38
21
25
6.97
The table reports the volumes of lending types and importance of destination countries for Austrian parent banks for 2012Q4.
It shows the unconsolidated cross-border claims, claims to affiliates, local subsidiary claims and consolidated total claims.
If a country does not host an affiliate, no value is shown for affiliate and subsidiary claims.
For banks with a frequency of < 4 per country, no exact count is shown due to data confidentiality requirements.
All figures are volumes in billion Euros.
22
Table 6: Lending channels: Cross-Border, to Affiliates and Subsidiaries Local Claims
Date
2005Q2
2005Q3
2005Q4
2006Q1
2006Q2
2006Q3
2006Q4
2007Q1
2007Q2
2007Q3
2007Q4
2008Q1
2008Q2
2008Q3
2008Q4
2009Q1
2009Q2
2009Q3
2009Q4
2010Q1
2010Q2
2010Q3
2010Q4
2011Q1
2011Q2
2011Q3
2011Q4
2012Q1
2012Q2
2012Q3
2012Q4
Banks
Claims
365
190.28
374
195.35
371
197.00
371
218.87
376
216.63
377
226.32
378
237.11
376
247.82
377
261.11
380
254.59
378
261.98
381
278.58
382
294.10
384
303.72
382
279.70
382
276.32
382
270.03
382
274.92
384
257.87
384
264.33
384
265.90
380
255.81
377
239.52
377
251.56
373
249.71
372
250.38
371
243.72
371
246.67
369
240.48
369
235.87
367
231.27
Unconsolidated
Affiliates
by Subsidiaries
Affiliates Loans Subsidiaries Local Claims
114
34.65
66
82
119
35.92
69
88
131
41.54
73
96
138
44.08
74
100
143
46.46
76
109
149
50.45
75
112
157
46.43
73
112
174
63.87
82
150
178
72.83
82
160
184
72.22
84
175
193
79.79
88
192
199
82.44
88
205
201
88.46
87
217
201
82.94
84
231
204
92.03
84
224
202
90.13
83
212
201
90.35
84
209
207
82.17
85
201
209
75.75
84
200
213
79.80
84
205
217
80.36
84
208
218
69.76
84
198
227
72.63
86
203
234
76.39
87
201
238
74.93
87
201
237
72.96
86
201
237
69.43
86
201
237
65.65
86
203
232
64.86
87
209
234
62.41
87
207
229
57.39
84
207
Consolidated
Parents
Banks Claims
49
313.36
48
323.03
48
342.89
51
374.45
51
378.16
52
387.08
51
411.54
51
462.93
51
483.72
54
493.66
55
516.15
56
542.88
60
578.46
60
622.85
61
554.29
63
543.02
64
531.12
63
528.73
64
506.95
65
516.19
64
519.08
61
491.91
62
484.17
65
503.24
61
510.05
61
516.78
61
507.56
62
516.17
60
515.28
59
508.83
59
503.24
The table reports the volumes of the different lending channels. The same data is represented graphically in figure 2a.
It shows the unconsolidated cross-border claims, claims to affiliates, local subsidiary claims and consolidated claims.
The volumes are in billion Euros.
23
Table 7: Not Winsorised Summary Statistics for Austrian Banks over 2005Q2 to 2012Q4
Percent (unless otherwise specified)
Austrian-owned parent Banks
No affiliates(n=118)
Variable
Mean
Median
SD
Foreign-owned parent Banks
With foreign affiliates(n=25)
Mean
Median
SD
No affiliates(n=32)
Mean
Median
SD
With affiliates(n=11)
Mean
Median
SD
Balance sheet data (for each bank / and quarter i)
24
Observations
Dependent Variables
∆ Liquid Assets/TA
∆ Domestic Loans/TA
∆ Foreign Loans/TA
∆ Net Due to Affiliates/TA
Independent Variables
Illiquid Assets/TA
Commitments/TA+Com
Real Assets (in BN Euros)
Real Assets 4Q 2012 (in BN Euros)
Deposits/Liabilities
Capital/TA
Foreign Loans/TA
Domestic Loans/TA
Deposits from Affiliates/TA
3,274
594
830
257
0.000
0.016
0.004
0.000
0.008
0.000
0.008
0.188
0.101
0.001
0.015
0.006
0.003
0.001
-0.007
0.000
0.006
0.002
0.000
0.000
0.000
0.009
0.132
0.078
0.026
0.011
0.126
0.003
0.011
0.035
-0.000
0.003
0.000
0.050
0.103
0.494
-0.001
0.004
0.014
0.004
0.007
-0.002
-0.000
0.000
0.008
0.001
0.000
0.000
0.015
0.045
0.068
0.060
0.055
0.023
0.756
0.085
2.891
3.222
0.567
0.097
0.069
0.711
0.760
0.079
0.865
0.994
0.645
0.095
0.026
0.723
0.128
0.043
5.830
5.789
0.252
0.061
0.196
0.243
0.685
0.096
17.185
16.273
0.357
0.088
0.182
0.524
0.036
0.708
0.094
8.074
7.597
0.325
0.080
0.183
0.511
0.010
0.152
0.045
24.051
23.918
0.209
0.073
0.126
0.224
0.097
0.806
0.096
1.236
1.187
0.500
0.091
0.468
0.450
0.902
0.032
0.732
0.559
0.617
0.047
0.394
0.355
0.230
0.139
1.406
1.629
0.383
0.165
0.605
0.360
0.583
0.078
27.803
19.274
0.341
0.098
0.417
0.184
0.039
0.612
0.048
3.254
4.246
0.346
0.084
0.390
0.114
0.008
0.184
0.076
46.176
37.540
0.261
0.071
0.237
0.176
0.081
(i) Source: OeNB.
(ii) Beginning of quarter assets are used to standardize growth in all dependent variables.
(iii) The data are observed quarterly from 2005Q1 to 2012Q4 for a panel of individual banks, which report unconsolidated figures.
(iv) The sample is restricted to banks with greater than 0.5 billion Euros in total assets (2012 prices) at least once in a quarter.
(v) The dependent variables are not winsorised at the 1st and 99th percentile.
(vi) To mitigate the effect of bank mergers on the dependent variable, banks are excluded in a particular quarter when asset growth exceeds 10%.
(vii) Affiliates include foreign branches and subsidiaries of Austrian parent banks.
Table 8: Domestic and Cross-border Lending Activities - AT (passive) Ownership
firm characteristics’ effects on growth in domestic and cross-border total loans (to banks and non-banks) for
parent banks without affiliates (upper panel) and parent banks with affiliates (lower panel) that are owned by
Austrian institutions. The underlying fixed effects regressions of quarterly growth in total loans on Libor-Ois,
central bank facility access, firm characteristics, and interactions are presented in appendix 7. Beginning of
quarter assets are used to standardize growth in loans. The data are observed quarterly from 2005Q1 to
2012Q4 for a panel of individual banks, which report unconsolidated figures. The panel is restricted to banks
with greater than 0.5 billion Euros in total assets (2012 prices) at least once in a quarter during the sample
period. To mitigate the effect of bank mergers on the dependent variable, banks are excluded in a particular
quarter when asset growth exceeds 10%. Firm characteristics data comes from a variety of supervisory data
sources provided by OeNB. The Libor-Ois is the quarterly average of the daily difference between the London
Interbank Offered Rate and the effective federal funds rate. Growth variables are winsorized at the 1st and
99th percentiles. Standard errors are clustered by bank. ***, **, and * respectively indicate significance at
the 1%, 5%, and 10% level.
Panel A: Austrian Parent Banks without Affiliates - AT (passive) Ownership
∆ Domestic Loans
∆ Loans/Assets
Illiquid Assets
Commitment
Log Real Assets
Deposits
Capital
Observations
Number of Banks
R2 within
R2 between
R2 overall
Time fixed effects
Bank fixed effects
Not Utilized
0.042
-0.113
0.003
0.012
0.068
3,034
114
0.083
0.095
0.008
Yes
Yes
Utilized
-0.042
-0.153*
0.007*
-0.018
0.253*
Difference
-0.083*
-0.040
0.004
-0.031
0.186
Not Utilized
-0.012
0.025
0.001
-0.020
0.090
2,975
112
0.119
0.000
0.003
Yes
Yes
Utilized
0.017
0.118*
-0.002
-0.003
-0.080
Difference
0.029*
0.078
-0.003
0.017
-0.017
Panel B: Austrian Parent Banks with Affiliates - AT (passive) Ownership
∆ Domestic Loans
∆ Loans/Assets
Illiquid Assets
Commitment
Log Real Assets
Deposits
Capital
Net Due To
Observations
Parent Banks
R2 within
R2 between
R2 overall
Time fixed effects
Bank fixed effects
Not Utilized
-0.033
0.318**
-0.012
-0.036
-0.297
0.134
562
25
0.234
0.002
0.022
Yes
Yes
Utilized
-0.056
0.067
-0.014*
-0.043
-0.112
0.297*
Difference
-0.023
-0.251
-0.002
-0.007
0.184
0.163
25
Not Utilized
0.003
0.160
-0.013**
-0.071
-0.022
-0.164
562
25
0.191
0.111
0.002
Yes
Yes
Utilized
0.062*
-0.152
-0.003
-0.069*
-0.035
-0.109*
Difference
0.059
-0.312*
0.010*
0.002
-0.013
0.055
Table 9: Cross-border Lending Activities of Banks - AT (passive) Ownership
firm characteristics’ effects on growth in cross-border loans to banks (upper panel) for parent banks without
affiliates and banks with affiliates. Affiliates are foreign branches and foreign subsidiaries of parent banks. The
sample includes only parent banks with Austrian ownership, parent banks with non-Austrian ownership are
excluded (passive ownership). The underlying fixed effects regressions of quarterly growth in loans to banks
on Libor-Ois, central bank facility access, firm characteristics, and interactions are presented in appendix 7.
Beginning of quarter assets are used to standardize growth in loans. The data are observed quarterly from
2005Q1 to 2012Q4 for a panel of individual banks, which report unconsolidated figures. The panel is restricted
to banks with greater than 0.5 billion Euros in total assets (2012 prices) at least once in a quarter during
the sample period. To mitigate the effect of bank mergers on the dependent variable, banks are excluded
in a particular quarter when asset growth exceeds 10%. Firm characteristics data comes from a variety of
supervisory data sources provided by OeNB. The Libor-Ois is the quarterly average of the daily difference
between the London Interbank Offered Rate and the effective federal funds rate. Growth variables are
winsorized at the 1st and 99th percentiles. Standard errors are clustered by bank. ***, **, and * respectively
indicate significance at the 1%, 5%, and 10% level.
Panel C: Austrian Parent Banks without Affiliates and with Affiliates - AT (passive) Ownership
∆ Loans
Not Utilized
Utilized
Difference
Not Utilized
Utilized
Difference
Illiquid Assets
Commitment
Log Real Assets
Deposits
Capital
Net Due To
-0.008
-0.014
0.000
-0.009
0.069
0.004
0.078
-0.003
0.010*
-0.098
0.011*
0.092*
-0.003
0.019*
-0.167
-0.09
0.113*
-0.011*
-0.036
-0.002
-0.135
-0.001
0.016*
-0.005*
0.050
-0.116**
-0.080*
0.008
-0.097
0.006
-0.014
-0.114
0.055
Observations
Parent Banks
R2 within
R2 between
R2 overall
Time fixed effects
Bank fixed effects
2,981
113
0.113
0.001
0.006
Yes
Yes
562
25
0.184
0.006
0.016
Yes
Yes
Panel D: Austrian Parent Banks with Affiliates - AT (passive) Ownership
∆ Net Due
Illiquid Assets
Commitment
Log Real Assets
Deposits
Capital
Net Due To
Observations
Parent Banks
R2 within
R2 between
R2 overall
Time fixed effects
Bank fixed effects
Not Utilized
0.026
-0.005
-0.005
-0.006
0.084
-0.122
562
25
0.132
0.389
0.001
Yes
Yes
Utilized
-0.045
-0.082
0.005
0.007
-0.028
-0.216*
Difference
-0.072
-0.077
0.009*
0.013
-0.112
-0.094
26
Figure 5: Geographical Distribution of Lending Activities
(i) Figure 5a shows the volumes of cross-border loans to European destination countries weighted by destination
country’s GDP. The difference to figure 1a lies in the weighting and the resulting perspective for the lendee.
(ii) Figure 5b shows the volumes of local claims from the perspective of the subsidiary country. This means a
foreign, majority owned subsidiary of an Austrian parent bank lending in it’s own country and cross-border.
(a) Geographical Distribution of Cross-Border Total Loans
Loans(as share of GDP)
0 - .001 (63)
.001 - .01 (35)
.01 - .1 (24)
.1 - 1 (5)
No data (127)
(b) Geographical Distribution of Local Subsidiary Claims
Local Claims
by Subsidiaries
(in bn Euros)
50 - 100 (2)
100 - 1000 (6)
1000 - 10000 (11)
10000 - 55000 (7)
No data (84)
27
Figure 6: Magnitudes of Balance Sheet Positions of the Austrian Banking Sector I
(i) Figure 6a shows the volume of total assets in billion Euros for Austrian parent institutions in the estimation
sample (186 banks). (ii) It distinguishes between banks without affiliates (solid line) and with affiliates (dashed
line). (iii) Figure 6b shows the median of commitments over the sum of commitments and total liabilities for
Austrian parent institutions. (iv) It distinguishes between banks without affiliates (solid line) and with affiliates
(dashed line).
2
ec
n-
D
Ju
-2
20
01
12
01
1
-2
D
ec
n20
11
0
D
Ju
ec
01
-2
01
0
09
D
Ju
ec
n2
-2
0
09
8
20
00
-2
ec
D
Ju
n-
08
7
20
nJu
20
D
ec
-2
n-
-2
Ju
D
00
07
6
00
06
20
ec
n-
-2
Ju
ec
D
Ju
n-
20
00
05
5
200
Volume in bn Euros
400
300
500
600
(a) Total Assets in Billion Euros
28
2
ec
-2
01
12
D
01
1
Ju
n20
ec
-2
D
0
11
Ju
n20
ec
-2
01
01
0
D
09
Ju
n2
09
ec
-2
0
D
00
8
Ju
n20
8
ec
-2
D
n20
0
Ju
00
7
06
07
ec
-2
D
Ju
n20
00
6
05
ec
-2
0
D
Ju
n2
ec
-2
0
D
Ju
n2
00
5
.07
Median Share of Commitments
.09
.1
.08
.11
(b) Commitment Ratio over Commitments and Total Liabilities
Figure 7: Magnitudes of Balance Sheet Positions of the Austrian Banking Sector II
(i) Figure 7a shows the median of non-bank deposits over total liabilities for Austrian parent institutions in
the estimation sample (186 banks). (ii) It distinguishes between banks without affiliates (solid line) and with
affiliates (dashed line). (iii) Figure 7b shows the median of liquid assets (cash and bonds) over total assets
for Austrian parent institutions. (iv) It distinguishes between banks without affiliates (solid line) and with
affiliates (dashed line).
2
D
ec
-2
20
01
12
01
1
nJu
D
ec
-2
11
0
n20
Ju
01
n2
ec
D
Ju
ec
D
-2
01
0
09
-2
0
09
8
20
00
-2
20
ec
D
Ju
n-
08
7
nJu
D
ec
-2
00
07
6
n-
-2
Ju
ec
D
Ju
20
00
06
20
n-
-2
D
Ju
ec
n-
20
00
05
5
.3
Median Share of non-Bank Deposits
.4
.5
.6
.7
(a) Deposits Ratio over Total Liabilities
29
2
01
2
ec
-2
01
D
Ju
n2
20
11
ec
-
20
11
D
Ju
n-
-2
01
0
9
-2
01
0
ec
D
Ju
n
ec
-2
00
D
00
9
Ju
n2
20
08
-2
00
8
-2
00
7
ec
D
Ju
n
00
7
ec
D
-2
00
6
n2
Ju
D
ec
20
0
6
5
Ju
n-
ec
-2
00
D
Ju
n
-2
00
5
.02
Median Share of Liquid Assets
.03
.04
.05
(b) Liquid Assets over Total Assets
Figure 8: Magnitudes of Balance Sheet Positions of the Austrian Banking Sector III
(i) Figure 8a shows the median of subscribed capital over total liabilities for Austrian parent institutions in
the estimation sample (186 banks). (ii) It distinguishes between banks without affiliates (solid line) and with
affiliates (dashed line). (iii) Figure 8b shows the volume of net-due to and net-due from in billion Euros Austrian
parent institutions with affiliates (36 banks). (iv) It distinguishes between net-due to affiliates (dashed line),
net-due to branches (dotted line) and net-due to subsidiaries (dash-dotted line).
2
D
ec
-2
20
01
12
01
1
Ju
D
ec
n-
-2
11
0
n20
Ju
01
n2
ec
D
Ju
ec
D
-2
01
0
09
-2
0
09
8
20
D
ec
Ju
n-
-2
20
00
08
7
nJu
D
ec
-2
00
07
6
-2
nJu
ec
D
20
00
06
20
Ju
n-
-2
D
Ju
ec
n-
20
00
05
5
.06
Median Capital Ratio
.07
.08
.09
.1
(a) Capital Ratio over Total Assets
Affiliates
Branches
Subsidiaries
30
2
01
2
ec
-2
01
D
Ju
n2
1
20
11
ec
-2
01
D
Ju
n-
-2
01
0
-2
01
0
ec
D
Ju
n
-2
00
9
D
ec
00
9
8
Ju
n2
-2
00
8
20
07
ec
-2
00
D
Ju
n
7
ec
D
-2
00
6
n20
0
Ju
D
ec
20
06
Ju
n-
ec
-2
D
Ju
n-
20
0
5
00
5
0
Volume in bn Euros
40
60
20
80
(b) Total Volume of Net Due
Figure 9: Additional Aspects of the Austrian Banking Sector
(i) Figure 9a shows the distribution of individual shares over the percentile distribution for 2012Q4. (ii) Figure
9a includes the median share of total loans over total assets for 2012Q4 (short dashed line). (iii) Figure 9a
differentiates between domestic and cross-border shares over total assets (red is domestic, blue is cross-border).
(iv) The 5 largest Austrian banks answer to the following Bank Lending Survey question: How have the
following factors affected your bank’s credit standards as applied to the approval of loans or credit lines to
enterprizes? (i) Costs related to your bank’s capital position, (ii) your bank’s ability to access market financing,
(iii) your bank’s liquidity position. A considerable tightening of credit standards is assigned a value of -1, and
a slight tightening a value of -0.5. Accordingly, a considerable easing of credit standards has the value of 1 and
a slight easing the value of 0.5.
(a) Distribution Shares of Loans Q4 2012
0
.2
Shares of Loans
.4
.6
.8
1
Cross-Border and Domestic Loans of AT Parent Banks
0
.2
.4
.6
.8
1
Cross-Border Percentiles
Domestic Percentiles
Domestic Aggregated Share
Cross-Border Aggregated Share
(b) Bank Lending Survey: Question about Refinancing Costs
-1
-.5
0
.5
1
Aggregated Answers to Bank Lending Survey by AT parent banks
1
2
3
2005
4
1
2
3
2006
4
1
2
3
2007
4
1
2
3
2008
4
1
2
3
2009
Capital position
4
1
2
3
2010
4
1
2
3
2011
4
1
2
3
2012
Ability to access market financing
Liquidity position
31
4
1
2
3
2013
Table 10: Austrian Banking Rescue Packages
Bank
Type State Intervention
Date
Amount Bn. Euros
Kommunalkredit Austria AG
State liability
State liability
Takeover
Recapitalization
Recapitalization
State liability
Recapitalization
State liability
State liability
Takeover
Recapitalization
State liability
Takeover
Recapitalization
Recapitalization
State liability
Recapitalization
State liability
Recapitalization
State liability
Recapitalization
State liability
21.11.2008
08.07.2009
05.01.2009
17.11.2009
30.11.2009
28.01.2009
15.12.2009
24.07.2009
30.12.2009
30.12.2009
29.12.2008
09.02.2009
04.07.1905
03.04.2009
27.10.2008
23.12.2009
23.12.2009
23.01.2009
10.03.2009
05.02.2009
27.03.2009
01.11.2008
7.508
1
2
0.22
0.03
8.765
0.135
1.35
0.3
4
1.35
3
KA Finanz AG
Hypo Alpe Adria AG (HAAI)
Oesterr.Volksbanken AG (VBAG)
Constantia Privatbank AG
BAWAG PSK
Erste Group Bank AG
Raiffeisen Zentralbank Oesterreich AG (RZB)
Oesterreichische Clearing Bank
1
0.4
0.4
0.55
6
1.224
4.25
1.75
4
(i) Source: Bericht des Rechnungshofes.
(ii) The total volume of the Austrian banking rescue measures was initially 100 billion Euros.
32
Table 11: Variables definitions
Liquid assets
Commitments
Austria
Source
Government Securities
All Countries
+ Cash
Undrawn credit facilities
Off balance items
Medium risk
Medium/low risk
Low risk
23
23
15
Loans
Loans to banks
23
23
23
23
23
approximated
Loans to non-banks
Intragroup lending
Credit
Illiquid assets
Loans to Branches
Loans to Subsidiaries
Commitments + Loans
Loans to banks
23
23
23
23
23
Loans to non-banks
Capital
Deposits
Liabilities
Intragroup liabilities
1. Subscribed capital
+ reserves
+ risk adjustments
+ value adjustments
- loss
2. Tier 1 capital
Deposit liabilities
by banks
by non-banks
All deposits
Debt securities
Capital and reserves
remaining liabilities
Deposits by Branches
Deposits by Subsidiaries
80
23
23
23
23
23
23
23
23
approximated
1
23 refers to data positions from the OeNB EZB-MONSTAT Statistics 23
15 refers to data positions from the OeNB VERA Beleg 15
3
80 refers to data positions from the OeNB VERA Beleg 80
4
Definition of loans/deposits according to the Regulation (EC) No 25/2009.
See also DefBalanceItems.pdf.
5
Definition of commitments according to Council Directive 2006/46/EC. See
also DefOffBalanceItems.pdf. MFI credit lines shall be defined as ”Undrawn
credit facilities” (”Medium risk”, ”Medium/low risk” and ”Low risk”).
2
33
Index of Working Papers:
January 30,
2009
Claudia Kwapil,
Johann Scharler
149 Expected Monetary Policy and the
Dynamics of Bank Lending Rates
February 5,
2009
Thomas Breuer,
Martin Jandač ka,
Klaus Rheinberger,
Martin Summer
150 How to find plausible, severe, and useful
stress scenarios
February 11,
2009
Martin Schneider,
Christian Ragacs
151 Why did we fail to predict GDP during the
last cycle? A breakdown of forecast errors
for Austria
February 16,
2009
Burkhard Raunig,
Martin Scheicher
152 Are Banks Different? Evidence from the
CDS Market
March 11,
2009
Markus Knell,
Alfred Stiglbauer
153 The Impact of Reference Norms on Inflation
Persistence When Wages are Staggered
May 14, 2009
Tarek A. Hassan
154 Country Size, Currency Unions, and
International Asset Returns
May 14, 2009
Anton Korinek
155 Systemic Risk: Amplification Effects,
Externalities, and Policy Responses
May 29, 2009
Helmut Elsinger
156 Financial Networks, Cross Holdings, and
Limited Liability
July 20, 2009
Simona Delle Chiaie
157 The sensitivity of DSGE models’ results to
data detrending
November 10,
2009
Markus Knell
Helmut Stix
158 Trust in Banks?
Evidence from normal times
and from times of crises
November 27,
2009
Thomas Scheiber
Helmut Stix
159 Euroization in Central, Eastern and Southeastern Europe – New Evidence On Its
Extent and Some Evidence On Its Causes
January 11,
2010
Jesús Crespo
Cuaresma
Martin Feldircher
160 Spatial Filtering, Model Uncertainty and the
Speed of Income Convergence in Europe
March 29,
2010
Markus Knell
161 Nominal and Real Wage Rigidities.
In Theory and in Europe
May 31, 2010
Zeno Enders
Philip Jung
Gernot J. Müller
162 Has the Euro changed the Business Cycle?
August 25,
2010
Marianna Č ervená
Martin Schneider
163 Short-term forecasting GDP with a DSGE
model augmented by monthly indicators
September 8,
2010
Sylvia Kaufmann
Johann Scharler
164 Bank-Lending Standards, the Cost Channel
and Inflation Dynamics
September 15,
2010
Helmut Elsinger
165 Independence Tests based on Symbolic
Dynamics
December 14,
2010
Claudia Kwapil
166 Firms' Reactions to the Crisis and their
Consequences for the Labour Market.
Results of a Company Survey conducted in
Austria
May 10, 2011
Helmut Stix
167 Does the Broad Public Want to Consolidate
Public Debt? – The Role of Fairness and of
Policy Credibility
May 11, 2011
Burkhard Raunig,
Johann Scharler
168 Stock Market Volatility, Consumption and
Investment; An Evaluation of the Uncertainty
Hypothesis Using Post-War U.S. Data
May 23, 2011
Steffen Osterloh
169 Can Regional Transfers Buy Public
Support? Evidence from EU Structural
Policy
May 23, 2011
Friederike Niepmann
Tim Schmidt-Eisenlohr
170 Bank Bailouts, International Linkages and
Cooperation
September 1,
2011
Jarko Fidrmuc,
Mariya Hake,
Helmut Stix
171 Households’ Foreign Currency Borrowing in
Central and Eastern Europe
September 9,
2011
Jürgen Eichberger,
Klaus Rheinberger,
Martin Summer
172 Credit Risk in General Equilibrium
October 6,
2011
Peter Lindner
173 Decomposition of Wealth and Income using
Micro Data from Austria
October 18,
2011
Stefan Kerbl
174 Regulatory Medicine Against Financial
Market Instability:
What Helps And What Hurts?
December 31,
2011
Konstantins Benkovskis 175 How Does Quality Impact on Import Prices?
Julia Wörz
January 17,
2012
Nicolás Albacete
176 Multiple Imputation in the Austrian
Household Survey on Housing Wealth
January 27,
2012
Gerhard Fenz,
Lukas Reiss,
Martin Schneider
177 A structural interpretation of the impact of
the great recession on the Austrian
economy using an estimated DSGE model
July 27,
2012
Helmut Stix
178 Why Do People Save in Cash? Distrust,
Memories of Banking Crises, Weak
Institutions and Dollarization
August 20,
2012
Markus Knell
179 Increasing Life Expectancy and Pay-AsYou-Go Pension Systems
September 25,
2012
Fabio Rumler,
Walter Waschiczek
180 Have Changes in the Financial Structure
Affected Bank Protability? Evidence for
Austria
November 9,
2012
Elisabeth Beckmann,
Jarko Fidrmuc,
Helmut Stix
181 Foreign Currency Loans and Loan Arrears
of Households in Central and Eastern
Europe
June 10,
2013
Luca Fornaro
182 International Debt Deleveraging
June 10,
2013
Jenny Simon,
Justin Valasek
183 Efficient Fiscal Spending by Supranational
Unions
July 24,
2013
Thomas Breuer, HansJoachim Vollbrecht,
Martin Summer
184 Endogenous Leverage and Asset Pricing in
Double Auctions
September 23,
2013
Martin Feldkircher
185 A Global Macro Model for Emerging Europe
September 25,
2013
Martin Gächter,
Aleksandra Riedl
186 One Money, One Cycle? The EMU
Experience
December 9,
2013
Stefan Niemann,
Paul Pichler
187 Collateral, Liquidity and Debt Sustainability
March 6,
2014
Elisabeth Beckmann,
Helmut Stix
188 Foreign currency borrowing and knowledge
about exchange rate risk
March 10,
2014
Jesús Crespo
Cuaresma,
Martin Feldkircher,
Florian Huber
189 Forecasting with Bayesian Global Vector
Autoregressive Models:
A Comparison of Priors
May 12,
2014
Claudia Steinwender
190 Information Frictions and the Law of One
Price: “When the States and the Kingdom
became United”
May 12,
2014
Saleem A. Bahaj
191 Systemic Sovereign Risk: Macroeconomic
Implications in the Euro Area
May 16,
2014
John Bagnall,
David Bounie,
Kim P. Huynh,
Anneke Kosse,
Tobias Schmidt,
Scott Schuh and
Helmut Stix
192 Consumer Cash Usage: A Cross-Country
Comparison with Payment Diary Survey
Data
May 19,
2014
Konstantins Benkovskis 193 “Made in China” - How Does it Affect
Julia Wörz
Measures of Competitiveness?
June 25,
2014
Burkhard Raunig,
Johann Scharler and
Friedrich Sindermann
194 Do Banks Lend Less in Uncertain Times?
July 28,
2014
Martin Feldkircher and
Florian Huber
195 The International Transmission of U.S.
Structural Shocks – Evidence from Global
Vector Autoregressions
September 16,
2014
Kim P. Huynh,
Philipp SchmidtDengler,
Helmut Stix
Martin Brown,
Helmut Stix
196 The Role of Card Acceptance in the
Transaction; Demand for Money
October 17,
2014
Ludmila Fadejeva,
Martin Feldkircher,
Thomas Reininger
198 Spillovers from Euro Area and U.S. Credit
and Demand Shocks: Comparing Emerging
Europe on the Basis of a GVAR Model
December 18,
2014
Esther Segalla
199 Shock Transmission through International
Banks: Austria
October 10,
2014
197 The Euroization of Bank Deposits in Eastern
Europe
Call for Entries:
Visiting Research Program
The Oesterreichische Nationalbank (OeNB) invites applications from external researchers
for participation in a Visiting Research Program established by the OeNB’s Economic
Analysis and Research Department. The purpose of this program is to enhance
cooperation with members of academic and research institutions (preferably post-doc)
who work in the fields of macroeconomics, international economics or financial
economics and/or with a regional focus on Central, Eastern and Southeastern Europe.
The OeNB offers a stimulating and professional research environment in close proximity
to the policymaking process. Visiting researchers are expected to collaborate with the
OeNB’s research staff on a prespecified topic and to participate actively in the
department’s internal seminars and other research activities. They will be provided with
accommodation on demand and will, as a rule, have access to the department’s computer
resources. Their research output may be published in one of the department’s publication
outlets or as an OeNB Working Paper. Research visits should ideally last between 3 and 6
months, but timing is flexible.
Applications (in English) should include
− a curriculum vitae,
− a research proposal that motivates and clearly describes the envisaged research
project,
− an indication of the period envisaged for the research visit, and
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Applications for 2014/2015 should be e-mailed to eva.gehringer-wasserbauer@oenb.at by
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Applicants will be notified of the jury’s decision by mid-June. The following round of
applications will close on November 1, 2015.

Shock Transmission through International Banks: Austria

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